A-mote

LowZee

RFID reader

Building automation

Processing Streaming Sensor Data

Through ABDF

One of the major Advantage of AIoTm is that users can directly push their streaming sensor/device data for processing onto the in-built analytics framework ABDF (www.abdf.in). It is also possible for the users to query their IoT enabled devices/sensors on the fly to get current status. Users need not have to do programming, instead can use dynamic dashboard facility to define the data streams and then monitor the data generated. it is also possible for them to define thresholds and configure alerts. Data is pushed onto the secure message queues with topic based security enabled. This will ensure that right people get visibility to those data sets through appropriate authentication techniques, despite having to share the same queue with other users.
The whole idea of building ABDF was to make Data Mining more accessible to those spectrum of users outside the range of Data scientists. ABDF is intended to narrow the gap between regular BI and Data Mining world. Besides all a novice user will struggle to build a mining processing pipeline incorporating all the required elements to ensure that the output is reliable. ABDF have built in Algorithm Templates that can help build any mining process flow easily. One can then reshape the template to fine tune the results. A well integrated visualization engine will make life a lot easier for its users in visualizing the result sets.